Such an electric impedance tomography device (EIT device) is known, for example, from EP 1 000 580 A1, which is used to record an “electric impedance tomogram” of a chest cross section of a patient.
Electric impedance tomography is a method for the reconstruction of impedance distributions, more precisely, of impedance changes relative to a reference distribution, in electrically conductive bodies. A plurality of electrodes are arranged for this purpose on the surface of the body to be examined. A ring-shaped, equidistant array of 16 electrodes, which can be laid around the chest of a patient with a belt, is used in typical cases. The control and analyzing unit also has analog electric circuits for signal amplification and for feeding alternating current and electronic circuits for digitizing and preprocessing the voltage signals as well as a digital signal processor for controlling the device and for processing the recorded data to reconstruct the impedance distribution. The control and analyzing unit ensures that a pair (preferably) of adjacent electrodes are consecutively supplied with an electric alternating current (e.g., 5 mA at 50 kHz) and the electric voltages are detected at the remaining electrodes by the control and analyzing unit (it is also possible, conversely, to feed an alternating voltage to one electrode pair and to measure the alternating currents over a plurality of remaining electrode pairs); the voltages of all remaining pairs of adjacent electrodes are typically detected, but it is also possible, in principle, to omit individual electrodes, as a result of which information is, however, lost. The impedance change, more precisely, the impedance change relative to a reference distribution (e.g., the impedance distribution during the first recording) can be reconstructed with algorithms from the totality of all measured signals during the consecutive current feeds, during which the position of the feeding electrode pair migrates step by step about the electrode ring. The impedance distribution, more precisely the change in impedance relative to a reference distribution (e.g., the impedance distribution during the first recording) can be reconstructed with algorithms from all the measured signals during the consecutive current feeds, during which the position of the feeding electrode pair migrates step by step around the electrode ring. The prior-art algorithms furnish as the reconstruction result a matrix of 32×32 image elements, wherein the matrix contains for each image element the reconstructed impedance change for that image element. A plurality of such matrices are recorded during each breath at preset time intervals. These are displayed consecutively on a display, as a result of which the intratidal changes in impedance distribution over time are made visible practically as a film (movie).
Electric impedance tomography of the chest for measuring the regional lung ventilation has been increasingly used in research-focused intensive care. Theoretical models and experimental comparisons of EIT with CT images of the chest show a nearly complete proportionality of the air content in the lung tissue to the impedance thereof. The breaths are resolved in space with about 20% of the chest diameter and in time typically with about 20 to about 40 matrices per second, which makes bedside monitoring of the regional lung ventilation possible. The matrices are occasionally also called images of the impedance distribution (with 32×32=1024 image elements) or frames.
Consequently, a sequence of impedance changes, which is also called time series of impedance change values for the given image element, is determined for each image element over one phase of inspiration or expiration. The terms “impedance change values and impedance change curves” will be used synonymously below, even though a time series consisting of discrete points is not a curve in the strict sense of the word. The time series are also represented in the form of curves as functions of time in the views for reasons of representation.
One essential advantage of the high frame rate is that the breaths, especially their inspiration and expiration phases, can be resolved in time. It is therefore possible to only analyze the regional distribution of the ventilated air in the end-inspiratory status (tidal image), but also to investigate the changes over time during the inspiration and expiration in order to infer regional lung mechanical processes therefrom. For example, local inspiration curves are determined, for example, in the article “Regional ventilation delay index: Detection of tidal recruitment using electric impedance tomography,” T. Muders et al., Vincent J. L., Editor, Yearbook of Intensive Care and Emergency Medicine, and the time at which it has reached 40% of its maximum, is related for each local inspiration curve with the global inspiration time and an image or faster or slower regions with lower or higher time constants than the average is generated therefrom. A “regional ventilation delay index (RVD)” is defined from this as an indicator of the inhomogeneity over time.
One more step is taken in EP 2 228 009 A1 and the global inspiration or expiration phase is divided into a plurality of equidistant volume steps and the intratidal variations (ITV), i.e., the redistribution of the ventilated partial volumes per volume step, into so-called “regions of interest” (ROI), which comprise a defined number of image elements, is determined. The result is then shown in curves specific of the ROIs over equidistant volume steps or variables coupled therewith. It is thus determined which lung areas contain more or less air than the other areas at which time during inspiration or expiration. In the ideal case, which is homogeneous over time, everything remains constant. By contrast, there are redistributions in lungs that are inhomogeneous over time. The advantage of the greater division of the respiration flanks of the ITV compared to the viewing of the one, 40% threshold value in RVD is that curves are viewed over ROIs that are coarser in space and, unlike in RVD, curves rather than an image that would be visually accessible in a simple manner are available. Moreover, inhomogeneities over time may possibly be overlooked due to unfavorable selection of the ROIs. Furthermore, no global ITV parameter analogous to the RVD index, which would show upon first glance whether redistributions are present, is defined.